[PDF] Top 20 Extending Machine Translation Evaluation Metrics with Lexical Cohesion to Document Level
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Extending Machine Translation Evaluation Metrics with Lexical Cohesion to Document Level
... of lexical cohesion to translation quality, so as to identify, apart from its use frequency, other significant aspects for MT evaluation at the docu- ment ...of cohesion devices in a ... See full document
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Bilingual Lexical Cohesion Trigger Model for Document Level Machine Translation
... links, cohesion has been explored in the literature of both linguistics and computational ...linguistics. Cohesion is defined as relations of meaning that exist within the text and divided into grammatical ... See full document
5
When a Good Translation is Wrong in Context: Context Aware Machine Translation Improves on Deixis, Ellipsis, and Lexical Cohesion
... Though machine translation errors caused by the lack of context beyond one sentence have long been acknowledged, the development of context-aware NMT systems is hampered by several ...standard ... See full document
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Document Level Machine Translation Evaluation with Gist Consistency and Text Cohesion
... (2012), cohesion is another important element to organize ...less lexical cohesion devices than those of human ...Here lexical cohesion devices mainly refer to content words reiterating ... See full document
8
Lexical Chain Based Cohesion Models for Document Level Statistical Machine Translation
... the lexical cohesion structure of a ...two lexical chain based co- hesion models to incorporate lexical cohesion into document-level statistical machine trans- ... See full document
11
Has Machine Translation Achieved Human Parity? A Case for Document level Evaluation
... cost, machine translation quality is typically assessed by means of crowd- ...automatic metrics and “very similar” to ratings produced by “experts” 2 (Callison-Burch, ...on machine ... See full document
6
Contrastive Lexical Evaluation of Machine Translation
... candidate translation. As with exist- ing evaluation metrics, target words from the reference can only be matched once, and flexible matching may be in- troduced, based on lemmas, synsets (Lavie and ... See full document
5
Metrics for Evaluation of Word level Machine Translation Quality Estimation
... of machine translation (MT) is a task of determining the quality of an au- tomatically translated text without any oracle (ref- erence) ...word level (Luong et al., 2014), sentence level (Shah ... See full document
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Document Level Machine Translation with Word Vector Models
... automatic evaluation obtained with the Asiya toolkit (Gonz´alez et ...several lexical metrics (BLEU, NIST, TER, ME- TEOR and ROUGE), a syntactic metric based on the overlap of PoS elements (SP-Op), ... See full document
8
Improving Evaluation of Document level Machine Translation Quality Estimation
... for document-level QE, the question arose if the assessment should also include an assessment of the fluency of documents (in addition to ade- quacy), as in Graham et ...reference translation in the ... See full document
6
Lexical Chains meet Word Embeddings in Document level Statistical Machine Translation
... the lexical chains in the source and next generate the target lexical chains that are used by their cohesion ...target lexical chains, they train MaxEnt classifiers — one per unique source ... See full document
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Modifications of Machine Translation Evaluation Metrics by Using Word Embeddings
... and document level, which allows them to compute the similarity between two sequence of ...use document-level embeddings as features and METEOR score as target to predict the adequacy of ... See full document
9
Accurate Evaluation of Segment level Machine Translation Metrics
... for evaluation of MT systems and document-level metrics have been iden- tified (Koehn, 2004; Graham and Baldwin, 2014; Graham et ...segment-level metrics, and it is unfortu- ... See full document
9
Automatic Evaluation of Chinese Translation Output: Word Level or Character Level?
... English-to-Chinese translation task evaluated 127 documents with 1,830 ...system translation, while the fluency score indicates how fluent a system translation ... See full document
6
Novel Document Level Features for Statistical Machine Translation
... Table 4 shows the new MT output of the two ex- ample sentences. Three LDC features are fired for mrsy in the 2nd sentence: hmrsy,AlmSry,Morsii, hmrsy,mHmd,Morsii and hmrsy,ySf,Morsii where the 3rd one is a false alarm. ... See full document
5
MT Evaluation: Human Like vs Human Acceptable
... We use the data from the Openlab 2006 Initiative 1 promoted by the TC-STAR Consortium 2 . This test suite is entirely based on European Parlia- ment Proceedings 3 , covering April 1996 to May 2005. We focus on the ... See full document
8
Better Evaluation Metrics Lead to Better Machine Translation
... Parameter tuning is carried out using Z- MERT (Zaidan, 2009). TER and BLEU are al- ready implemented in the publicly released version of Z-MERT, and Z-MERT’s modular design makes it easy to integrate TESLA-M and TESLA-F ... See full document
10
Multi level Evaluation for Machine Translation
... We use the latest version of Meteor, i.e. Me- teor Universal (Denkowski and Lavie, 2014) in this paper. Meteor computes a one-to-one align- ment between matching words in a translation and a reference. The space ... See full document
5
ORANGE: a Method for Evaluating Automatic Evaluation Metrics for Machine Translation
... its machine translations, and its reference translations, we compute the average rank of the reference translations within the combined machine and reference translation ...statistical machine ... See full document
7
Combining Coherence Models and Machine Translation Evaluation Metrics for Summarization Evaluation
... 2011 metrics and our three met- rics on both initial and update ...our metrics with a circle on these ...4b, evaluation metrics al- ways correlate better on the initial task than on the update ... See full document
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